Memory Search
You have two tools for recalling information from your memory files. Use them.
Tools
memory_search
Semantic vector search across your indexed memory files (MEMORY.md, memory/*.md, and session transcripts).
Parameters:
| Param | Type | Required | Description |
|---|
query | string | yes | Natural language question or topic to search for |
maxResults | number | no | Max results to return (default: 6) |
minScore | number | no | Minimum relevance score threshold (0-1) |
Example calls:
{ "query": "what projects is the human working on" }
{ "query": "preferences about code style", "maxResults": 3 }
{ "query": "important dates birthdays deadlines", "maxResults": 10, "minScore": 0.3 }
Returns: Array of results, each with:
snippet — the matching text chunkpath — relative file path (e.g. MEMORY.md, memory/2026-02-07.md)startLine / endLine — line range in the source filescore — relevance scorecitation — formatted source reference (in direct chats)
memory_get
Read a specific section of a memory file by path and line range. Use this after memory_search to pull more context around a result.
Parameters:
| Param | Type | Required | Description |
|---|
path | string | yes | Relative path from workspace (e.g. MEMORY.md, memory/2026-02-07.md) |
from | number | no | Starting line number |
lines | number | no | Number of lines to read |
Example calls:
{ "path": "MEMORY.md" }
{ "path": "memory/2026-02-07.md", "from": 15, "lines": 30 }
When to Use Memory Search
Always search before answering about:
- Prior conversations or decisions
- The human's preferences, habits, or opinions
- Dates, deadlines, birthdays, events
- Project status or history
- Anything the human said "remember this" about
- Todos, action items, or commitments
- People, names, relationships
The pattern is:
- Receive a question that might involve past context
- Call
memory_search with a relevant query
- Review the results
- If a snippet looks promising but needs more context, call
memory_get with the path and line range
- Answer using what you found (cite sources in direct chats)
When NOT to Use
- Purely factual questions with no personal context ("what is Python?")
- The human explicitly gives you all the context you need in the message
- You just searched and the results are still in your context
Tips
- Be specific in queries. "birthday" works better than "important information about the human."
- Search multiple angles. If one query returns nothing useful, try rephrasing. "project deadlines" and "what's due soon" might return different results.
- Don't over-fetch. Start with default maxResults. Only increase if you need more coverage.
- Use memory_get sparingly. The search snippets are usually enough. Only pull full sections when you need surrounding context.
- Say when you checked. If you searched and found nothing, tell the human: "I checked my memory and didn't find anything about that." Don't silently guess.
What Gets Indexed
Your memory search covers:
MEMORY.md — your curated long-term memorymemory/*.md — daily notes and raw logs- Session transcripts (if enabled)
These files are automatically indexed. You don't need to trigger indexing — just write to the files and the system handles the rest.
Do NOT
- Do NOT try to run shell commands like
cat or ls to read memory files. Use memory_search and memory_get.
- Do NOT try to configure or debug the search system. That's operator config, not your job.
- Do NOT assume memory is empty without searching first. The index may have content even if the
memory/ directory looks sparse.
